Nathan Reed

Architected and productionized LangGraph-based multi-step AI agent workflows for legal research and compliance use cases, including extraction, validation, conflict detection, retention schedule generation, and human-in-the-loop reviewer approval with full auditability and versioned decision provenance. Built hybrid RAG pipelines combining semantic embeddings, keyword/BM25 search, and metadata filtering (e.g., jurisdiction and document type) across vector stores (pgvector, Pinecone, Weaviate) to improve source-grounded retrieval and traceability. Implemented structured output generation with JSON schema/Pydantic validation, confidence scoring per claim, unsupported-claim detection, and conflict/consistency checks to reduce hallucinations. Delivered multi-tenant SaaS capabilities (Next.js, FastAPI, PostgreSQL, Redis, Docker, AWS) including RBAC, audit logs, review queues, and export-ready reporting.

Engineered production RAG pipelines over legal, financial, operational, and policy corpora using OpenAI embeddings and hybrid semantic + keyword (BM25) retrieval with pgvector and metadata filters for precise, source-traceable retrieval. Designed multi-step agent workflows (research → retrieval → extraction → validation → structured generation) incorporating confidence scoring, citation mapping, unsupported-claim detection, and JSON schema-enforced outputs. Added defensible validation layers and human-in-the-loop review checkpoints to improve stakeholder trust and suitability for regulated enterprise environments.

Built and maintained production applications using React/TypeScript/JavaScript with Python/Node.js API-driven backends and structured data workflows. Integrated AI APIs and prompt-based services for structured processing, automation, search, and user-facing product features. Developed and supported authentication/private user workflows, REST APIs, webhooks, and third-party integrations. Improved rendering performance via caching and optimized image delivery. Supported production reliability through Docker, CI/CD, monitoring, debugging, and release workflows across cloud platforms such as GCP/AWS/Azure/Firebase, plus edge tooling like Cloudflare and deployment workflows like Vercel.